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» Learning Mixtures of Gaussians
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GECCO
2009
Springer
101views Optimization» more  GECCO 2009»
16 years 1 months ago
Modeling UCS as a mixture of experts
We present a probabilistic formulation of UCS (a sUpervised Classifier System). UCS is shown to be a special case of mixture of experts where the experts are learned independentl...
Narayanan Unny Edakunni, Tim Kovacs, Gavin Brown, ...
VLSISP
1998
111views more  VLSISP 1998»
15 years 6 months ago
Quantitative Analysis of MR Brain Image Sequences by Adaptive Self-Organizing Finite Mixtures
This paper presents an adaptive structure self-organizing finite mixture network for quantification of magnetic resonance (MR) brain image sequences. We present justification fo...
Yue Wang, Tülay Adali, Chi-Ming Lau, Sun-Yuan...
BIOINFORMATICS
2010
108views more  BIOINFORMATICS 2010»
15 years 4 months ago
Mass spectrometry data processing using zero-crossing lines in multi-scale of Gaussian derivative wavelet
Motivation: Peaks are the key information in Mass Spectrometry (MS) which has been increasingly used to discover diseases related proteomic patterns. Peak detection is an essentia...
Nha Nguyen, Heng Huang, Soontorn Oraintara, An P. ...
ICML
2005
IEEE
16 years 7 months ago
Predicting probability distributions for surf height using an ensemble of mixture density networks
There is a range of potential applications of Machine Learning where it would be more useful to predict the probability distribution for a variable rather than simply the most lik...
Michael Carney, Padraig Cunningham, Jim Dowling, C...
ICDM
2010
IEEE
264views Data Mining» more  ICDM 2010»
15 years 4 months ago
Block-GP: Scalable Gaussian Process Regression for Multimodal Data
Regression problems on massive data sets are ubiquitous in many application domains including the Internet, earth and space sciences, and finances. In many cases, regression algori...
Kamalika Das, Ashok N. Srivastava